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LLM framework LISTEN aids multi-objective decision-making

By PulseAugur Editorial · [1 sources] ·

Researchers have developed LISTEN, a new framework that uses Large Language Models (LLMs) to help users make complex decisions with multiple competing objectives. The framework employs iterative algorithms to refine the LLM's understanding of implicit preferences, reducing the cognitive load of traditional decision-making processes. Evaluated on tasks like flight booking and shopping, LISTEN demonstrated effectiveness in aligning LLM decisions with user goals. AI

IMPACT Provides a novel approach for LLMs to assist in complex decision-making tasks by learning implicit user preferences.

RANK_REASON The cluster contains an academic paper detailing a new framework and algorithms. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM framework LISTEN aids multi-objective decision-making

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The cluster contains an academic paper detailing a new framework and algorithms. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Adam S. Jovine, Tinghan Ye, Francis Bahk, Jingjing Wang, Matthew Ford, David B. Shmoys, Peter I. Frazier ·

    LISTEN to Your Preferences: An LLM Framework for Multi-Objective Selection

    arXiv:2510.25799v3 Announce Type: replace Abstract: Human experts often struggle to select the best option from a large set of items with multiple competing objectives, a process bottlenecked by the difficulty of formalizing complex, implicit preferences. To address this, we intr…

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